Who Will Train Us For The Million Net Jobs AI Will Create?

AI and smaller-scopes levels of automation continue to replace more tasks impinged to human labor before now. It should not feel sudden. It is a result of a deliberate and documented process spearheaded by technology centers like Silicon Valley and their relentless quest to add immense amounts of value, over the course of decades. It seems not everyone got the memo. Millions of people in jobs no human is supposed to be doing today or soon enough watch as their skills turn obsolete. In another predictable warning sign, a recent report by Gartner (see press release) forecasts that AI will continue to wreak havoc at varying rates depending on the industry. Even if by 2025 the net job surplus could reach the millions, doubts remain on the jobs and fields it will benefit, and to whose expense.

In terms of industries, some show a direr impact and in more evident ways than others. Gartner reports shrinking prospects in manufacturing, while healthcare and the public sector jobs may live to fight another 9-to-5. Of course, history has shown how technological effects can have unexpected ramifications in relatively short periods of time.

In terms of hierarchies, the extremes should be spared, with the middle levels hit the hardest. As it matures, AI tends to “eat out” job duties in its neighborhood, in a manner curiously similar to the pedagogical model proposed by developmental psychologist Lev Vygotsky he called “Zones of Proximal Development.” Upper management roles will still be awarded to humans, but low-skilled, entry-level duties too, as AI takes care of the hardest parts of jobs where human interaction is ultimately preferred.

As the case above and the report highlight, the role of AI will not always suppose a perfect replacement of humans. In fact, the complementary relationship, called “AI Augmentation,” is likely to become the most usual role of AI in the economy, at least for the next decade.

Educational demands of the future behind schedule

All things considered, skilling programs have at least three possible routes, the success of each highly dependent on the specifics of the case.

Specialized AI builders. It amounts to “teaching to teach AI”. General-purpose AI engineers and computer scientists will continue to be in high demand, the specific conditions and requirements of which not feasibly met by more than a single-digit percentage of people. But applying newer generations of AI into given industries can cast a wider net. Workers whose positions have an expiration date would “sleep with the enemy” and help develop the tool that will take over them. A more optimistic reframing of this process highlights the productivity increases of a given job, where the professional can acquire new skills thanks to the presence of the AI and achieve what was not possible before, possibly a best-case scenario of Augmentation as a path to job creation.

“Interfacers” and advocates. The prospects of AI evolution almost take development of its human-legible interfaces for granted. But for the time being, other humans will remain as the entry point towards AI for the rest of the race. This is true on the utilitarian level, of specific tasks AI can do for you; as well as­ in a higher, almost philosophical sense, where humans dispel myths, stave off fears, and in general spread the word on AI in more aspects of personal, social and political lives.

Move as far away from AI as possible. As robots take over the results-driven parts of life, humans could be free to pursue the aspects that makes them quintessentially human and might take longer for AI to recreate. There are a few promising, if anecdotal hints in this sense, such as the growth of the “orange industries.” YouTube seems to increase the incomes for its creators, and crowdfunding platforms such as Patreon offer creators hard to imagine for a less productive age. Don’t discard a new, more inclusive human Reinassance in creative, performing and philosophical endeavors.